Review: Fundamentals of Data Analytics in Python

The tutorial starts from the basics showing how to install Python and its data analysis libraries. Then it continues explaining the main uses that data scientists and engineers practice during their analysis: importing and cleaning data, vectorial computing, visualization and data summarization.

Most of the videos are commented sessions of IPython notebook sometimes supported by some slides. The authors go deep into the explanation of how to use the libraries for the manipulation of the data (Numpy, Scipy and Pandas), while they summarize the potential of the other complementary libraries. In particular, the last video is a survey of various visualization tools.

In conclusion, this video tutorial provides a solid introduction to the main tools for data analysis in Python and a clear view of the open source Python tools relevant to scientific and engineering programming. This tutorial seems perfect for people who need to learn the technical methodologies for data analysis and for people who already know Python but want to acquire skills about data analysis.